[GH-PAGES] Updated website
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@@ -231,13 +231,13 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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vector-add-performance:
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size Triton Torch
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0 4096.0 9.540372 9.600000
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0 4096.0 9.600000 9.600000
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1 8192.0 19.200000 19.200000
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2 16384.0 31.999999 38.400001
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3 32768.0 63.999998 63.999998
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2 16384.0 38.400001 38.400001
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3 32768.0 76.800002 76.800002
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4 65536.0 127.999995 127.999995
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5 131072.0 219.428568 219.428568
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6 262144.0 384.000001 341.333321
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6 262144.0 384.000001 384.000001
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7 524288.0 472.615390 472.615390
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8 1048576.0 614.400016 614.400016
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9 2097152.0 722.823517 722.823517
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@@ -254,7 +254,7 @@ We can now run the decorated function above. Pass `print_data=True` to see the p
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 11.322 seconds)
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**Total running time of the script:** ( 0 minutes 11.053 seconds)
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.. _sphx_glr_download_getting-started_tutorials_01-vector-add.py:
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@@ -302,15 +302,15 @@ We will then compare its performance against (1) :code:`torch.softmax` and (2) t
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N Triton Torch (native) Torch (jit)
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0 256.0 512.000001 546.133347 186.181817
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1 384.0 585.142862 585.142862 153.600004
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2 512.0 630.153853 606.814814 154.566038
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2 512.0 655.360017 606.814814 154.566038
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3 640.0 682.666684 640.000002 160.000000
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4 768.0 702.171410 664.216187 163.839992
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.. ... ... ... ...
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93 12160.0 812.359066 406.179533 199.038365
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94 12288.0 812.429770 415.661740 199.399583
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94 12288.0 812.429770 415.661740 199.298541
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95 12416.0 810.840807 412.149375 198.954424
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96 12544.0 810.925276 412.971190 199.209928
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97 12672.0 809.389265 412.097543 199.264875
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96 12544.0 810.925276 412.971190 199.111113
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97 12672.0 811.007961 412.097543 199.167004
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[98 rows x 4 columns]
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@@ -328,7 +328,7 @@ In the above plot, we can see that:
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 1 minutes 12.703 seconds)
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**Total running time of the script:** ( 1 minutes 12.704 seconds)
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.. _sphx_glr_download_getting-started_tutorials_02-fused-softmax.py:
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@@ -462,37 +462,37 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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matmul-performance:
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M cuBLAS ... Triton Triton (+ LeakyReLU)
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0 256.0 2.730667 ... 2.978909 2.978909
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0 256.0 2.978909 ... 2.978909 2.978909
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1 384.0 7.372800 ... 8.507077 8.507077
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2 512.0 14.563555 ... 15.420235 15.420235
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2 512.0 14.563555 ... 16.384000 16.384000
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3 640.0 22.260869 ... 24.380953 24.380953
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4 768.0 32.768000 ... 34.028308 34.028308
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5 896.0 39.025776 ... 40.140799 39.025776
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6 1024.0 49.932191 ... 53.773130 52.428801
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6 1024.0 49.932191 ... 52.428801 52.428801
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7 1152.0 44.566925 ... 46.656000 46.656000
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8 1280.0 51.200001 ... 56.888887 56.109587
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9 1408.0 64.138541 ... 64.902096 64.902096
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10 1536.0 80.430545 ... 76.933564 76.106321
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11 1664.0 63.372618 ... 62.492442 62.061463
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12 1792.0 72.983276 ... 70.246402 69.810085
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13 1920.0 68.098521 ... 69.467336 68.098521
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14 2048.0 73.262953 ... 75.234154 68.200062
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15 2176.0 82.473969 ... 80.173899 78.608000
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16 2304.0 68.251065 ... 73.501144 73.275679
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17 2432.0 71.305746 ... 81.669953 81.433227
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18 2560.0 77.833728 ... 76.382283 76.382283
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19 2688.0 84.108772 ... 81.928846 82.284288
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20 2816.0 81.827785 ... 78.021838 80.026067
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21 2944.0 82.921853 ... 78.358539 77.265163
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22 3072.0 81.238312 ... 83.638266 83.761985
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23 3200.0 84.432717 ... 89.887639 88.888888
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24 3328.0 82.275764 ... 82.088138 86.528001
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25 3456.0 81.600781 ... 84.954233 83.459178
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26 3584.0 86.623693 ... 92.032132 89.025140
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27 3712.0 85.091436 ... 82.833620 84.874549
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28 3840.0 85.136259 ... 86.806905 87.493673
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29 3968.0 92.935215 ... 88.103928 87.347124
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30 4096.0 93.727466 ... 85.217605 90.626421
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9 1408.0 64.138541 ... 64.902096 63.392744
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10 1536.0 79.526831 ... 76.106321 75.296679
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11 1664.0 62.929456 ... 62.061463 62.061463
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12 1792.0 72.983276 ... 69.810085 69.379162
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13 1920.0 66.461539 ... 70.530615 70.530615
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14 2048.0 73.908442 ... 75.234154 74.898285
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15 2176.0 83.500614 ... 79.540109 79.226957
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16 2304.0 68.446623 ... 73.501144 73.275679
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17 2432.0 71.305746 ... 82.388456 81.908060
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18 2560.0 78.019048 ... 77.649287 75.502306
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19 2688.0 84.108772 ... 80.537273 83.369354
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20 2816.0 84.035084 ... 79.298560 79.298560
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21 2944.0 82.373605 ... 80.122235 79.483304
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22 3072.0 79.415291 ... 81.355034 83.146995
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23 3200.0 78.817733 ... 90.140846 86.021503
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24 3328.0 83.034941 ... 87.474238 84.397770
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25 3456.0 81.849303 ... 84.244062 85.950501
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26 3584.0 87.211821 ... 94.548254 94.947616
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27 3712.0 84.159518 ... 89.755028 88.797643
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28 3840.0 84.356981 ... 81.499296 83.027026
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29 3968.0 86.114283 ... 82.504353 87.850207
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30 4096.0 93.206754 ... 89.717734 89.538177
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[31 rows x 5 columns]
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@@ -502,7 +502,7 @@ We can now compare the performance of our kernel against that of cuBLAS. Here we
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 2 minutes 10.117 seconds)
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**Total running time of the script:** ( 2 minutes 12.872 seconds)
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.. _sphx_glr_download_getting-started_tutorials_03-matrix-multiplication.py:
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@@ -5,12 +5,12 @@
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Computation times
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=================
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**03:34.142** total execution time for **getting-started_tutorials** files:
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**03:36.629** total execution time for **getting-started_tutorials** files:
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:10.117 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_03-matrix-multiplication.py` (``03-matrix-multiplication.py``) | 02:12.872 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.703 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_02-fused-softmax.py` (``02-fused-softmax.py``) | 01:12.704 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.322 | 0.0 MB |
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| :ref:`sphx_glr_getting-started_tutorials_01-vector-add.py` (``01-vector-add.py``) | 00:11.053 | 0.0 MB |
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+---------------------------------------------------------------------------------------------------------+-----------+--------+
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